[1] Wang B W, Wang L, Yu C Y, et al. Long-distance BOTDA sensing systems using video-BM3D denoising for both static and slowly varying environment[J]. Opt. Express, 2019, 27(25): 36100-36113.

[2] Zeng K Y, Yang G J, Liu S, et al. Enhanced BOTDA sensors based on Brillouin phase recovery using Kramers-Kronig relation[J]. IEEE Sensors J., 2021, 21(20): 22775-22782.

[4] Voskoboinik A, Yilmaz O F, Willner A W, et al. Sweep-free distributed Brillouin time-domain analyzer (SF-BOTDA)[J]. Opt. Express, 2011, 19(26): B842-B847.

[5] Zhou D P, Peng W, Chen L, et al. Brillouin optical time-domain analysis via compressed sensing[J]. Opt. Lett., 2018, 43(22): 5496-5499.

[6] Chu Q, Wang B Z, Wang H N, et al. Fast Brillouin optical time-domain analysis using frequency-agile and compressed sensing[J]. Opt. Lett., 2020, 45(15): 4365-4368.

[7] Zhou D P, Ning W K, Shu D Y, et al. Performance enhancement of Brillouin sensing systems based on compressive sampling[J]. OSA Continuum, 2020, 3(11): 3116-3124.

[8] Wu H, Tan H X, Shen L, et al. Sparse representation of Brillouin spectrum using dictionary learning[J]. Opt. Express, 2020, 28(12): 18160-18171.

[9] Aharon M, Elad M, Bruckstein A. K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation[J]. IEEE Trans. on Signal Processing, 2006, 54(11): 4311-4322.

[17] Tropp J A, Gilbert A C. Signal recovery from random measurements via orthogonal matching pursuit[J]. IEEE Trans. on Information Theory, 2007, 53(12): 4655-4666.